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关键词： computer vision education   staged framework   computational thinking   data science   symbolic AI   neural network-based AI  

摘要： Computer vision education is increasingly important in modern technology curricula;yet, it often lacks a systematic approach integrating both theoretical concepts and practical applications. This study proposes a staged framework for computer vision education designed to progressively build learners' competencies across four levels. This study proposes a four-staged framework for computer vision education, progressively introducing concepts from basic image recognition to advanced video analysis. Validity assessments were conducted twice with 25 experts in the field of AI education and curricula. The results indicated high validity of the staged framework. Additionally, a pilot program, applying computer vision to acid-base titration activities, was implemented with 40 upper secondary school students to evaluate the effectiveness of the staged framework. The pilot program showed significant improvements in students' understanding and interest in both computer vision and scientific inquiry. This research contributes to the AI educational field by offering a structured, adaptable approach to computer vision education, integrating AI, data science, and computational thinking. It provides educators with a structured guide for implementing progressive, hands-on learning experiences in computer vision, while also highlighting areas for future research and improvement in educational methodologies.

关键词： Interdisciplinary research   Co-authorship network   Egocentric network   Professional network   Exploration strategy  

摘要： To identify collaboration trends with coauthors, this paper elaborates a theoretical framework by introducing a measure to quantify exploration of the author in joining teams of coauthors with respect to the extreme exploration possibilities. Using the clustering coefficient, we gauge the team exploration from the author-centric vista evaluating configuration values of the ego networks. This value is normalized with respect to the maximum exploration possibilities for the author facilitating us to derive a measure, viz., the team exploration score for the team exploration strategy. We further derive a dynamical version of this measure. The average profiles of the exploration strategies are compared for the authors from the USA, England, and India publishing in a rapidly growing and collaboration-extensive field, viz. artificial intelligence in computer science, in the time window from 1990 to 2020. The bibliometric data are sourced from the Clarivate Web of Science. Configuration values are evaluated in the ascending year of publications in year-long time windows to compute the team exploration score for each author. Our analysis shows that the annually averaged profiles of authors corresponding to the three countries are almost constantly increasing toward high team exploration scores. Also, in the career-averaged profiles, authors publishing more than 20 papers have mostly adopted exploratory strategies.

关键词： Location awareness   Software   History   Vectors   Computer science   Codes   Aggregates   Heterogeneous graph   change history   call relationship   fault localization   attention mechanism  

摘要： Automated software fault localization has become one of the hot spots on which researchers have focused in recent years. Existing studies have shown that learning-based techniques can effectively localize faults leveraging various information. However, there exist two problems in these techniques. The first is that they simply represent various information without caring the contribution of different information. The second is that the data imbalance problem is not considered in these techniques. Thus, their effectiveness is limited in practice. In this paper, we propose HetFL, a novel heterogeneous graph-based software fault localization technique to aggregate different information into a heterogeneous graph in which program entities and test cases are regarded as nodes, and coverage, change histories, and call relationships are viewed as edges. HetFL first extracts textual and structure information from source code as attributes of nodes and integrates them to form an attribute vector. Then, for a given node, HetFL finds its neighbor nodes based on the types of edges and aggregates corresponding neighbor nodes to form type vectors. After that, the attribute vector and all the type vectors of each node are aggregated to generate the final vector representation by an attention mechanism. Finally, we leverage a convolution neural network (CNN) to obtain the suspicious score of each method. To validate the effectiveness of HetFL, experiments are conducted on the widely used dataset Defects4J (v1.2.0). The experimental results show that HetFL can localize 217 faults within Top-1 that is 25 higher than the state-of-the-art technique DeepFL, and achieve 6.37 and 5.58 in terms of MAR and MFR which improve DeepFL by 9.0% and 5.6%, respectively. In addition, we also perform experiments on the latest version of Defects4J (v2.0.0). The experimental results show that HetFL has better performance than the baseline methods.

关键词： Computer science   artificial intelligence  

ISBN: (数字)9781394241903 ISBN: (纸本)9781394241873

摘要： This book provides a comprehensive exploration of the exciting intersection between technology and biology and delves into the principles, applications, and future directions of IoT in the realm of bioelectronics; it serves as both an introduction for those new to the field and as a detailed reference for experienced professionals seeking to deepen their knowledge.

关键词： Artificial intelligence  

摘要： This research explores the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications involving the human factor, such as social media and other interactive digital platforms. By providing deeper insights into elusive, unconscious aspects of communication, psychoanalytic methods can enhance content-centric applications like fake news detection and mental health diagnostics. Conversely, computer science, especially Artificial Intelligence (AI), can contribute quantitative concepts and methods to psychoanalysis, identifying patterns and emotional cues in human expression. In particular, this research aims to apply computer science methods to establish fundamental relationships between emotions and Lacanian discourses. Such relations are discovered in our approach via empirical investigation and statistical analysis, and are eventually validated in a theoretical (psychoanalytic) way. It is worth noting that, although emotions have been sporadically studied in Lacanian theory, to the best of our knowledge a systematic, detailed investigation of their role is missing. Such fine-grained understanding of the role of emotions can also make the identification of Lacanian discourses more effective and easy in practise. In particular, our methods indicate the emotions with highest differentiation power in terms of corresponding discourses;conversely, we identify for each discourse the most characteristic emotions it admits. As a matter of fact, we develop a method which we call Lacanian Discourse Discovery (LDD), that simplifies (via systematizing) the identification of Lacanian discourses in texts. Although the main contribution of this paper is inherently theoretical (psychoanalytic), it can also facilitate major practical applications in the realm of interactive digital systems. Indeed, our approach can be automated through Artificial Intelligence

关键词： Market culture   Innovation performance   Absorptive capacity   Resistance to change  

摘要： PurposeThis study aims to investigate the relationship between market culture and innovation performance and to reveal the role of absorptive capacity and resistance to change by building on the resource-based ***/methodology/approachData was gathered from 222 firm managers of manufacturing firms by using the survey method. Structural equation modeling and PROCESS macro were used to analyze the *** results indicate that market culture is positively related to innovation performance and absorptive capacity mediates this relationship. It is also found that resistance to change negatively moderates the relationship between market culture and innovation performance, but it has no moderating effect on the relationship between absorptive capacity and innovation ***/valuePrevious research examining the association between market culture and innovation performance is scarce and provides contradictory findings. This indicates that there is an underlying mechanism of this association neglected before. This study is an attempt to reconcile contradictory findings and enlighten the fuzzy areas of this relationship. Accordingly, this study focuses on absorptive capacity as a mediator and proves its role empirically. Moreover, this study is the first to examine the role of resistance to change and demonstrates its buffer role in the market culture-innovation performance link. It is also revealed that resistance to change does not moderate the relationship between absorptive capacity and innovation performance. The findings elucidate the underlying mechanism of the relationship between market culture and innovation performance, reconcile contradictory findings of extant research, expand the current knowledge, and provide practical implications.

摘要： Israeli military operations in Gaza have decimated child health, resulting in a “lost generation”. Sharmila Devi reports. “When I had to perform amputations on six children in one night was when I thought I was at breaking point”, Ghassan Abu Sitt...